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author | Marc Glisse <marc.glisse@inria.fr> | 2020-04-14 20:30:29 +0200 |
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committer | Marc Glisse <marc.glisse@inria.fr> | 2020-04-14 20:30:56 +0200 |
commit | acb9d5b9d1317d3d8168bc3ac46860d078abba84 (patch) | |
tree | 8cca1567dc12433432f87285fbe0dd1b4d0c97b2 /src/python/test/test_dtm.py | |
parent | 3f1e4bf5f139afe887ae501f20c5d3f40b5a6f79 (diff) |
Check that the gradient is not NaN
This can easily happen with pytorch, and there is special code to avoid
it.
Diffstat (limited to 'src/python/test/test_dtm.py')
-rwxr-xr-x | src/python/test/test_dtm.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/src/python/test/test_dtm.py b/src/python/test/test_dtm.py index db3e5df5..de74c42b 100755 --- a/src/python/test/test_dtm.py +++ b/src/python/test/test_dtm.py @@ -46,14 +46,14 @@ def test_dtm_compare_euclidean(): r6 = dtm.fit_transform(pts2) assert r6.detach().numpy() == pytest.approx(r0) r6.sum().backward() - assert pts2.grad is not None + assert pts2.grad is not None and not torch.isnan(pts2.grad).any() pts2 = torch.tensor(pts, requires_grad=True) assert pts2.grad is None dtm = DistanceToMeasure(k, implementation="ckdtree", enable_autodiff=True) r7 = dtm.fit_transform(pts2) assert r7.detach().numpy() == pytest.approx(r0) r7.sum().backward() - assert pts2.grad is not None + assert pts2.grad is not None and not torch.isnan(pts2.grad).any() def test_dtm_precomputed(): |